Globally top-notch companies are attempting to fight climate change through new technologies. Artificial intelligence (AI) and machine learning (ML) are now being used to combat and reverse the effects of climate change. The Intergovernmental Panel on Climate Change (IPCC), said to be the world’s leading scientific body on the climate crisis, has advised that emissions of accumulated greenhouse gases (GHGs) need to be cut in half by 2030 and reach net-zero emissions by 2050, to avoid the worst effects of global warming.
Microsoft believes that artificial intelligence, often encompassing machine learning and deep learning, is a “game changer” for climate change and environmental issues. The company’s AI for Earth program has committed $50 million over five years to create and test new applications for AI. Scientists across the world are working to improve environment conditions introducing technology in various domains.
Accuracy in weather forecasts:
Now identifying tropical cyclones, weather fronts and atmospheric rivers are easier. With the involvement of technology, scientists can help keep people safe from natural disasters to some extent. Green Horizons, an IBM research initiative, is using cognitive computing and the internet of things (IoT) to analyze climate change data. And AI has also helped researchers achieve 89 to 99 percent accuracy in weather forecasts.
Lots of experiments are being done to decrease the pollution level. Cognitive computing, with its superior data processing ability, is being paired with IoT to predict pollution rates in Beijing. The system uses ML to ingest data from sources such as meteorological satellites and traffic cameras to constantly learn and adjust the predictive models. It is able to forecast pollution 72 hours in advance, with an accuracy down to the nearest mile on where the pollution is coming from and where it will likely go.
Beijing is using this methodology to reduce pollution levels ahead of the 2022 Winter Olympics. It can use the predictions to implement policies like temporarily restricting industrial activity or limiting traffic and construction. It is modelling hypothetical what-if scenarios that will allow officials to test the effectiveness of such interventions.
In Singapore, a Digital Innovation Lab has been mastering emerging technologies to ensure the continuity of tech-based climate change initiatives. The lab is building technology that can optimize public transport routes and decrease carbon emissions from vehicles. It also has the technology to track the rise of sea levels and their impact on marine health. Another project is tracking food provenance, checking on the quality of nutrition and the chemical composition of food.
Reducing carbon dioxide:
The company Hypergiant is growing algae so it can absorb carbon dioxide and give off oxygen. The problem with naturally growing algae is that they can grow out of control. To solve this, scientists have developed an AI unit called the Eos Bioreactor that can regulate the growth of the algae and optimize their carbon-absorbing properties. The unit is the size of a refrigerator and is said to be 400 times more effective at capturing carbon than trees in the same unit area as the Eos Bioreactor.
Clean city planning:
Another IBM system in development could help cities plan for future heat waves. AI would simulate the climate at the urban scale and explore different strategies to test how well they ease heat waves. For example, if a city wanted to plant new trees, machine learning models could determine the best places to plant them to get optimal tree cover and reduce heat from pavement.
Hotter temperatures will have significant impacts on agriculture as well.
Data from sensors in the field that monitor crop moisture, soil composition and temperature help AI improve production and know when crops need watering. Incorporating this information with that from drones, which are also used to monitor conditions, can help increasingly automatic AI systems know the best times to plant, spray and harvest crops, and when to head off diseases and other problems. This will result in increased efficiency, enhanced yields, and lower use of water, fertilizer and pesticides. In India, AI has helped farmers get 30 percent higher groundnut yields per hectare by providing information on preparing the land, applying fertilizer and choosing sowing dates.